Journal of Inflammation Research (Sep 2022)

Nomogram Based on Inflammatory Biomarkers to Predict the Recurrence of Hepatocellular Carcinoma—A Multicentre Experience

  • Zheng Z,
  • Guan R,
  • Zou Y,
  • Jian Z,
  • Lin Y,
  • Guo R,
  • Jin H

Journal volume & issue
Vol. Volume 15
pp. 5089 – 5102

Abstract

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Zehao Zheng,1,2,* Renguo Guan,3,4,* Yiping Zou,1,2,* Zhixiang Jian,2 Ye Lin,2 Rongping Guo,3,4 Haosheng Jin2 1Shantou University Medical College, Shantou, People’s Republic of China; 2Department of General Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, People’s Republic of China; 3Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, People’s Republic of China; 4State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Rongping Guo, Department of Liver Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng East Road, Guangzhou, 510060, People’s Republic of China, Email [email protected] Haosheng Jin, Department of General Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, 510060, People’s Republic of China, Email [email protected]: Our study aimed to identify inflammatory biomarkers and develop a prediction model to stratify high-risk patients for hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) recurrence after curative resection.Patients and Methods: A total of 583 eligible HBV-HCC patients with curative hepatectomy from Guangdong Provincial People’s Hospital (GDPH) and Sun Ya-sen University Cancer Centre (SYSUCC) were enrolled in our study. Cox proportional hazards regression was utilized to evaluate potential risk factors for disease-free survival (RFS). The area under the receiver operating characteristic (ROC) curve (AUC) was utilized to assess the discrimination performance. Calibration plots and decision curve analyses (DCA) were used to evaluate the calibration of the nomogram and the net benefit, respectively.Results: Based on the systemic inflammation response index (SIRI), aspartate aminotransferase to neutrophil ratio index (ANRI), China Liver Cancer (CNLC) stage and microvascular invasion, a satisfactory nomogram was developed. The AUC of our nomogram for predicting 1-, 2-, and 3-year RFS was 0.767, 0.726, and 0.708 in the training cohort and 0.761, 0.716, and 0.715 in the validation cohort, respectively. Furthermore, our model demonstrated excellent stratification as well as clinical applicability.Conclusion: The novel nomogram showed a higher prognostic power for the RFS of HCC patients with curative hepatectomy than the CNLC, AJCC 8th edition and BCLC staging systems and may help oncologists identify high-risk HCC patients.Keywords: hepatocellular carcinoma, inflammatory biomarkers, nomogram, recurrence-free survival

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